(1) Field of Invention
The present invention relates to a distributed network optimization system and, more particularly, to a system implementing distributed particle swarm optimization that allows multiple nodes to cooperate in searching efficiently for a set of parameter values that optimizes overall network performance.
(2) Description of Related Art
The present invention is related to a network optimization system. Currently available network optimization systems utilize a “greedy” approach in which each node attempts to optimize its own performance without taking into consideration other nodes in the network. Such existing systems are known to be sub-optimal in that they do not optimize the global network.
In addition, work has been performed in the area of distributed global network optimization based on convex optimization and game theory. However, the disadvantage of convex optimization lies in its assumption that the utility function is convex, which is overly restrictive. Furthermore, game theoretic approaches have not yet demonstrated quality performance and lack a general framework for designing incentives for cooperative behavior.
Thus, a continuing need exists for a distributed network optimization system without central control which allows multiple nodes to cooperate in order to optimize overall network performance, while handling high dimensional, non-convex, and noisy global network utility functions.